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Exp. Statistics Unit, Box 9653, Mississippi State Univ., MS 39762
* Corresponding author (mcox{at}pss.msstate.edu)
Given the potential for high amounts of variability in yield-affecting soil factors, some soil property or properties may serve as a basis for site-specific soil management. The objectives of this study were to determine the variability of selected soil properties and to determine the relationships between these soil properties and soybean [Glycine max (L.) Merr.] yield. Soil samples were collected from the center point of 0.5-ha grids in three fields and were analyzed for soil-test-extractable Ca, Mg, K, P, pH in water, and texture. Relative elevation, slope, aspect, and soybean yield were also determined at these points. Coefficient of variation, Pearson correlation coefficients, and principal component (PC) analysis coupled with stepwise regression were used to analyze the data. Two of the three fields had medium to high P and K values but low yields while the third field had low P and K values but relatively higher yields, suggesting factors other than P and K levels were affecting yield. Soil variability, with the exception of pH, was highest in the North field. Potassium in this field exhibited evidence of high amounts of small-scale spatial or temporal variability. Across all three fields, pH had the lowest amount of variability while variability in soil fertility varied from year to year and field to field. Fertility parameters had to be considered with other soil factors to determine their relationship to yield. Topography-yield relationships varied from field to field. Areas with higher clay content in all three fields had higher yield, suggesting clay could be used as a basis for site-specific soil management.
Abbreviations: DGPS, differentially-corrected global positioning system • GIS, geographical information system • PC, principal component
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